Application of a multiscale maximum entropy image restoration algorithm to HXMT observations

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Ju Guan, Li-Ming Song and Zhuo-Xi Huo. Application of a multiscale maximum entropy image restoration algorithm to HXMT observations[J]. Chinese Physics C, 2016, 40(8): 086203. doi: 10.1088/1674-1137/40/8/086203
Ju Guan, Li-Ming Song and Zhuo-Xi Huo. Application of a multiscale maximum entropy image restoration algorithm to HXMT observations[J]. Chinese Physics C, 2016, 40(8): 086203.  doi: 10.1088/1674-1137/40/8/086203 shu
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Received: 2015-12-09
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    Supported by Strategic Priority Research Program on Space Science, Chinese Academy of Sciences (XDA04010300) and National Natural Science Foundation of China (11403014)

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Application of a multiscale maximum entropy image restoration algorithm to HXMT observations

    Corresponding author: Ju Guan,
  • 1.  Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
  • 2. Qian Xuesen Laboratory of Space Technology, China Academy of Space Technology, Beijing 100094, China
  • 3. Department of Physics, Tsinghua University, Beijing 100084, China
Fund Project:  Supported by Strategic Priority Research Program on Space Science, Chinese Academy of Sciences (XDA04010300) and National Natural Science Foundation of China (11403014)

Abstract: This paper introduces a multiscale maximum entropy (MSME) algorithm for image restoration of the Hard X-ray Modulation Telescope (HXMT), which is a collimated scan X-ray satellite mainly devoted to a sensitive all-sky survey and pointed observations in the 1-250 keV range. The novelty of the MSME method is to use wavelet decomposition and multiresolution support to control noise amplification at different scales. Our work is focused on the application and modification of this method to restore diffuse sources detected by HXMT scanning observations. An improved method, the ensemble multiscale maximum entropy (EMSME) algorithm, is proposed to alleviate the problem of mode mixing exiting in MSME. Simulations have been performed on the detection of the diffuse source Cen A by HXMT in all-sky survey mode. The results show that the MSME method is adapted to the deconvolution task of HXMT for diffuse source detection and the improved method could suppress noise and improve the correlation and signal-to-noise ratio, thus proving itself a better algorithm for image restoration. Through one all-sky survey, HXMT could reach a capacity of detecting a diffuse source with maximum differential flux of 0.5 mCrab.

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